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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

The manufacturing industry is in an unenviable position. Manufacturers are being called to reduce their carbon footprint, adopt circular economy practices and become more eco-friendly in general. And manufacturers face pressure to constantly innovate while ensuring stability and safety.

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5 ways IBM helps manufacturers maximize the benefits of generative AI

IBM Big Data Hub

While still in its early stages, generative AI can provide powerful optimization capabilities to manufacturers in the areas that matter most to them: productivity, product quality, efficiency, worker safety and regulatory compliance.

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Trying to tackle Big Data: European Union launches draft Data Act

Data Matters

The Data Act is intended to “ ensure fairness in the digital environment, stimulate a competitive data market, open opportunities for data-driven innovation and make data more accessible for all ”. Users may also request that their data are made available to third parties, sometimes even in real time.

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Win the connected and autonomous car race while protecting data privacy

Thales Cloud Protection & Licensing

To enable this revolution, automobile manufacturers and their supply chain partners have rapidly adopted new technologies to better serve customers and win competitive advantages: Embedding high-speed connectivity in vehicles to improve customer experience and entertainment as well as real-time diagnostics and OTA updates. Data security.

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The convergence of HPC and AI: Driving innovation at speed  

IBM Big Data Hub

In today’s rapidly changing landscape, delivering higher-quality products to the market faster is essential for success. However, in today’s market, consumers demand rapid releases of new models. Prolonged development cycles might harm automotive manufacturers’ sales and customer loyalty.

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Streamlining supply chain management: Strategies for the future

IBM Big Data Hub

On top of disruption, companies with global supply chains must also deal with different regulatory environments, cultural norms and market conditions. Big data and predictive analytics are increasingly being used to improve forecasting accuracy, allowing businesses to respond more effectively to changes in customer needs.

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How to build a successful product development strategy

IBM Big Data Hub

A finely tuned product development strategy is a holistic, cross-collaborative endeavor with the capacity to help any organization weather unforeseen events or market changes. With new markets and functionalities appearing almost overnight, product development can’t be a blind process.